Research on ultrasonic bone cutting mechanism based on extended finite element method.

The research on the crack propagation mechanism of bone has important research significance and clinical medical value for the selection of cutting parameters and the development of new surgical tools. In this paper, an extended finite element method (X-FEM) model of ultrasonic bone cutting considering microstructure was developed to further study the ultrasonic bone cutting mechanism and to quantitatively analyze the effects of cutting direction, ultrasonic parameters, and cutting parameters on the mechanism of ultrasonic bone cutting crack propagation. The results show that ultrasonic bone cutting is essentially a controlled crack propagation process, in which brittle crack and fatigue crack are the main crack propagation mechanisms. In order to improve the efficiency of ultrasonic bone cutting, large amplitude and high-frequency ultrasonic vibration are preferred. Compared with the other two cutting directions, the crack propagation deflection angle in the transverse cutting direction is the largest, resulting in the worst cutting surface. Therefore, in the path planning of orthopedic surgical robots, the transverse cutting direction should be avoided as much as possible. Frequency only has a significant effect on the crack propagation rate and has a positive correlation. There is a positive correlation between the deflection angle, propagation length, propagation rate, and amplitude, which provides the possibility to control the direction and length of crack propagation by controlling the amplitude of ultrasonic. The feed speed is much lower than the ultrasonic vibration speed, which makes the influence of ultrasonic vibration speed on the crack propagation characteristics dominant. The X-FEM model of ultrasonic bone cutting provides an effective method for selecting reasonable machining parameters of orthopedic robot and optimize the design of ultrasonic osteotome.

A powerful parent-of-origin effects test for qualitative traits on X chromosome in general pedigrees.

BACKGROUND: Genomic imprinting is one of the well-known epigenetic factors causing the association between traits and genes, and has generally been examined by detecting parent-of-origin effects of alleles. A lot of methods have been proposed to test for parent-of-origin effects on autosomes based on nuclear families and general pedigrees. Although these parent-of-origin effects tests on autosomes have been available for more than 15 years, there has been no statistical test developed to test for parent-of-origin effects on X chromosome, until the parental-asymmetry test on X chromosome (XPAT) and its extensions were recently proposed. However, these methods on X chromosome are only applicable to nuclear families and thus are not suitable for general pedigrees. RESULTS: In this article, we propose the pedigree parental-asymmetry test on X chromosome (XPPAT) statistic to test for parent-of-origin effects in the presence of association, which can accommodate general pedigrees. When there are missing genotypes in some pedigrees, we further develop the Monte Carlo pedigree parental-asymmetry test on X chromosome (XMCPPAT) to test for parent-of-origin effects, by inferring the missing genotypes given the observed genotypes based on a Monte Carlo estimation. An extensive simulation study has been carried out to investigate the type I error rates and the powers of the proposed tests. Our simulation results show that the proposed methods control the size well under the null hypothesis of no parent-of-origin effects. Moreover, XMCPPAT substantially outperforms the existing tests and has a much higher power than XPPAT which only uses complete nuclear families (with both parents) from pedigrees. We also apply the proposed methods to analyze rheumatoid arthritis data for their practical use. CONCLUSIONS: The proposed XPPAT and XMCPPAT test statistics are valid and powerful in detecting parent-of-origin effects on X chromosome for qualitative traits based on general pedigrees and thus are recommended.

Likelihood Ratio Test for Excess Homozygosity at Marker Loci on X Chromosome.

The assumption of Hardy-Weinberg equilibrium (HWE) is generally required for association analysis using case-control design on autosomes; otherwise, the size may be inflated. There has been an increasing interest of exploring the association between diseases and markers on X chromosome and the effect of the departure from HWE on association analysis on X chromosome. Note that there are two hypotheses of interest regarding the X chromosome: (i) the frequencies of the same allele at a locus in males and females are equal and (ii) the inbreeding coefficient in females is zero (without excess homozygosity). Thus, excess homozygosity and significantly different minor allele frequencies between males and females are used to filter X-linked variants. There are two existing methods to test for (i) and (ii), respectively. However, their size and powers have not been studied yet. Further, there is no existing method to simultaneously detect both hypotheses till now. Therefore, in this article, we propose a novel likelihood ratio test for both (i) and (ii) on X chromosome. To further investigate the underlying reason why the null hypothesis is statistically rejected, we also develop two likelihood ratio tests for detecting (i) and (ii), respectively. Moreover, we explore the effect of population stratification on the proposed tests. From our simulation study, the size of the test for (i) is close to the nominal significance level. However, the size of the excess homozygosity test and the test for both (i) and (ii) is conservative. So, we propose parametric bootstrap techniques to evaluate their validity and performance. Simulation results show that the proposed methods with bootstrap techniques control the size well under the respective null hypothesis. Power comparison demonstrates that the methods with bootstrap techniques are more powerful than those without bootstrap procedure and the existing methods. The application of the proposed methods to a rheumatoid arthritis dataset indicates their utility.